In a tower-type solar thermal power station, a heliostat reflects and gathers the sunlight irradiated onto its surface to a heat absorber, and then obtains solar energy through the heat absorber for power generation. In order to gather more energy on the surface of the heat absorber, the surface shape of each heliostat is a high-precision discrete curved surface with converging characteristics. There are many errors in the actual manufacturing process of heliostats, which will reduce the accuracy of the surface shape, affect the effect of sunlight convergence, and influence the effective energy obtained by the heat absorber. Therefore, it is necessary to accurately measure the surface shape of the heliostat to ensure the power generation efficiency of the tower-type solar thermal power station.
At present, the surface shape detection technology is mainly divided into contact type and non-contact type. The contact surface shape detection method is based on a displacement sensor or a probe and is not suitable for a precise optical mirror surface, and will exert a force on the mirror surface during detection, thus easily affecting the detection accuracy. The existing non-contact detection technology is based on stripe projection, which directly projects the stripe onto the surface of the object to be measured and calculates the heliostat surface shape through the bending and changes of the stripe. This method is suitable for objects with a diffuse reflecting surface, but it is difficult for the image collector to obtain effective stripe images when the reflectivity of the object surface is high, or even to complete the surface shape detection. The non-contact detection technique is to project the stripes onto the screen, then adjust the relative position between the heliostat and the screen, and finally calculate the heliostat surface shape by shooting the stripe image on the heliostat surface with an image collector. For this method, the relative positions among the image collector, the heliostat and the screen should be adjusted according to the heliostat before each detection, so as to obtain a complete stripe image; meanwhile, this method has higher requirements for the detection environment; the measured heliostat mirror is easily interfered by stray light, which affects the contrast and correctness of the stripe image. Therefore, there is a need for a high-precision and high-efficiency detection method which is able to detect the heliostat surface shape with high reflection characteristics.